CF Plugin Neural Coordination
Neural coordination plugin for multi-agent swarm intelligence using Self-Optimizing Neural Architecture (SONA), Graph Neural Networks (GNN), and attention mechanisms to optimize agent communication and decision-making.
Quick Command Reference
| Task | Command |
|---|---|
| Enable plugin | npx @claude-flow/cli@latest plugins toggle --enable neural-coordination |
| Disable plugin | npx @claude-flow/cli@latest plugins toggle --disable neural-coordination |
| Plugin info | npx @claude-flow/cli@latest plugins info neural-coordination |
| List tools | npx @claude-flow/cli@latest mcp tools |
| Check status | npx @claude-flow/cli@latest plugins list |
Installation
Via claude-flow: Already included with npx @claude-flow/cli@latest init
Standalone: npx @claude-flow/plugin-neural-coordination@latest
Activation
# Enable the plugin
npx @claude-flow/cli@latest plugins toggle --enable neural-coordination
# Verify activation
npx @claude-flow/cli@latest plugins info neural-coordination
Plugin Capabilities
SONA (Self-Optimizing Neural Architecture)
Adapts agent communication patterns in real-time (<0.05ms) based on task characteristics and agent performance, automatically adjusting routing weights.
npx @claude-flow/cli@latest mcp exec neural-coordination.sona \
--swarm-id my-swarm --action optimize --learning-rate 0.001
GNN (Graph Neural Network)
Models agent interactions as a graph and applies message-passing neural networks to learn optimal coordination strategies, improving context retrieval accuracy by ~12%.
npx @claude-flow/cli@latest mcp exec neural-coordination.gnn \
--swarm-id my-swarm --layers 3 --action predict-routing
Attention Mechanisms
Multi-head attention over agent outputs for weighted consensus, flash attention for large swarms (2.5-7.5x speedup), and cross-attention for inter-agent communication.
npx @claude-flow/cli@latest mcp exec neural-coordination.attention \
--swarm-id my-swarm --mode flash --heads 8
Swarm Topology Optimization
Analyzes current swarm topology and suggests optimal restructuring based on communication patterns and task requirements.
npx @claude-flow/cli@latest mcp exec neural-coordination.topology \
--swarm-id my-swarm --suggest --constraint latency
Common Patterns
Optimize Swarm Communication
npx @claude-flow/cli@latest plugins toggle --enable neural-coordination
npx @claude-flow/cli@latest mcp exec neural-coordination.sona \
--swarm-id my-swarm --action optimize
npx @claude-flow/cli@latest mcp exec neural-coordination.topology \
--swarm-id my-swarm --suggest
Neural-Enhanced Consensus
npx @claude-flow/cli@latest mcp exec neural-coordination.attention \
--swarm-id my-swarm --mode flash --consensus weighted
Train GNN on Historical Swarm Data
npx @claude-flow/cli@latest mcp exec neural-coordination.gnn \
--action train --data swarm-history.json --epochs 50
npx @claude-flow/cli@latest mcp exec neural-coordination.gnn \
--swarm-id my-swarm --action predict-routing
RAN DDD Context
Bounded Context: Agent Orchestration
References
- Command reference: See references/commands.md
- Full README
- npm